A reliable understanding of linkages between meteorological, hydrological and agricultural droughts (MD, HD and AD respectively) is crucial to building resilience and planning for future climate changes. Despite Australia being prone to severe droughts, lagtimes of propagation (and recovery) from meteorological to hydrological and agricultural droughts across its large hydroclimatic regions are not well understood. Therefore, we investigate the characteristics of drought propagation and recovery time lags for droughts of four timescales and a combination of drought onset and cessation criteria in 407 unregulated catchments within six major precipitation zones across Australia. We find that the propagation and recovery lags are dependent on climatic conditions, drought criteria and timescales. The average propagation times from MD to HD across Australia varied from 0.8 to 1.7 months for monthly timescales, increasing to 2 to 4.5 months for 12-monthly timescales. The corresponding recovery lagtimes were 1.3 to 3.7 and 1.7 to 7.5 months respectively. Similarly, the average propagation times from MD to AD ranged from 0.9 to 1.9 months for monthly timescales, increasing to 0.8 to 5 months for 12-monthly timescales. The corresponding recovery lagtimes were 0.7 to 2.8 and 0.3 to 9.4 months respectively. For droughts of smaller timescales, propagation and recovery lags are linearly correlated with recovery lagtimes consistently greater than the propagation times. As the timescale increases, these relationships weaken suggesting effects of other catchment attributes (e.g. groundwater contributions) on lag relationships. Notably, recovery lagtimes are generally longer for the high-yielding catchments in eastern Australia compared to the other regions

In the Lower Transboundary Indus Basin (LTIB), excessive groundwater is being consumed in combination with surface water to meet the increasing demand of irrigation, resulting in groundwater depletion that needs to be quantified. This study used GRACE (Gravity Recovery And Climate Experiment) satellite terrestrial water storage anomalies (TWSA) and Global Land Data Assimilation System (GLDAS) model data to produce monthly groundwater storage anomalies (GWSA) and to evaluate the depletion of groundwater storage in the LTIB. It is observed that the variation in GWSA exhibits a downward trend from 2003 to 2016. Additionally, TWSA and precipitation data depict seasonal characteristics with peaks in the summer and dips in the winter, which reflect variation in GWSA, respectively. GRACE TWSA measurements also detected massive floods that occurred in 2010 and 2015, and they significantly recharged groundwater in the LTIB. This study also utilized Empirical Orthogonal Function (EOF) analysis to assess the variance variability. The results revealed that more than 80% of total variance variability was explained by the first 2 EOF modes. The generalized three-cornered hat method (GTCH) was used to estimate the uncertainty of different GRACE TWSA measurements. The results show that groundwater storage is being depleted at a rate of 4.16 mm per year (2.97 km3 per year). Long-term monthly mean GRACE derived GWSA showed remarkable agreements with PCRaster Global Balance (PCR-GLOBWB) model 75% and WGHM (WaterGap Global Hydrological model) 81%. This study can be helpful to calculate the socio and agro-economic impact of the excessive withdrawal of groundwater.